The organization of the human cerebral cortex estimated by intrinsic functional connectivity
01 Sep 2011-Journal of Neurophysiology (American Physiological Society)-Vol. 106, Iss: 3, pp 1125-1165
TL;DR: In this paper, the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI data from 1,000 subjects and a clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex.
Abstract: Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
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TL;DR: Progress made during the first half of the Human Connectome Project project in refining the methods for data acquisition and analysis provides grounds for optimism that the HCP datasets and associated methods and software will become increasingly valuable resources for characterizing human brain connectivity and function, their relationship to behavior, and their heritability and genetic underpinnings.
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TL;DR: In this article, the authors studied functional brain organization in healthy adults using resting state functional connectivity MRI and proposed two novel brain wide graphs, one of 264 putative functional areas, the other a modification of voxelwise networks that eliminates potentially artificial short-distance relationships.
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TL;DR: Using multi-modal magnetic resonance images from the Human Connectome Project and an objective semi-automated neuroanatomical approach, 180 areas per hemisphere are delineated bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults.
Abstract: Understanding the amazingly complex human cerebral cortex requires a map (or parcellation) of its major subdivisions, known as cortical areas. Making an accurate areal map has been a century-old objective in neuroscience. Using multi-modal magnetic resonance images from the Human Connectome Project (HCP) and an objective semi-automated neuroanatomical approach, we delineated 180 areas per hemisphere bounded by sharp changes in cortical architecture, function, connectivity, and/or topography in a precisely aligned group average of 210 healthy young adults. We characterized 97 new areas and 83 areas previously reported using post-mortem microscopy or other specialized study-specific approaches. To enable automated delineation and identification of these areas in new HCP subjects and in future studies, we trained a machine-learning classifier to recognize the multi-modal 'fingerprint' of each cortical area. This classifier detected the presence of 96.6% of the cortical areas in new subjects, replicated the group parcellation, and could correctly locate areas in individuals with atypical parcellations. The freely available parcellation and classifier will enable substantially improved neuroanatomical precision for studies of the structural and functional organization of human cerebral cortex and its variation across individuals and in development, aging, and disease.
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TL;DR: It is found that motion-induced signal changes are often complex and variable waveforms, often shared across nearly all brain voxels, and often persist more than 10s after motion ceases, which increase observed RSFC correlations in a distance-dependent manner.
2,713Â citations
University of Western Ontario1, York University2, University of Bergen3, The Mind Research Network4, National Institutes of Health5, University of New Mexico6, University of Chieti-Pescara7, Washington University in St. Louis8, Stanford University9, Georgia Institute of Technology10, Oulu University Hospital11, Indiana University12, Otto-von-Guericke University Magdeburg13, Leibniz Institute for Neurobiology14
TL;DR: Emerging evidence suggests that dynamic FC metrics may index changes in macroscopic neural activity patterns underlying critical aspects of cognition and behavior, though limitations with regard to analysis and interpretation remain.
2,332Â citations
References
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TL;DR: Although parietal neurons represent objects in motor coordinates, visual responses are independent of the intention to perform specific motor acts, and the need for a single representation of space in environmental coordinates is eliminated.
Abstract: The space around us is represented not once but many times in parietal cortex. These multiple representations encode locations and objects of interest in several egocentric reference frames. Stimulus representations are transformed from the coordinates of receptor surfaces, such as the retina or the cochlea, into the coordinates of effectors, such as the eye, head, or hand. The transformation is accomplished by dynamic updating of spatial representations in conjunction with voluntary movements. This direct sensory-to-motor coordinate transformation obviates the need for a single representation of space in environmental coordinates. In addition to representing object locations in motoric coordinates, parietal neurons exhibit strong modulation by attention. Both topdown and bottom-up mechanisms of attention contribute to the enhancement of visual responses. The saliance of a stimulus is the primary factor in determining the neural response to it. Although parietal neurons represent objects in motor coordinates, visual responses are independent of the intention to perform specific motor acts.
1,589Â citations
TL;DR: This work identified the borders between several retinotopically organized visual areas in the posterior occipital lobe and estimated the spatial resolution of the fMRI signal and found that signal amplitude falls to 60% at a spatial frequency of 1 cycle per 9 mm of visual cortex.
Abstract: A method of using functional magnetic resonance imaging (fMRI) to measure retinotopic organization within human cortex is described. The method is based on a visual stimulus that creates a traveling wave of neural activity within retinotopically organized visual areas. We measured the fMRI signal caused by this stimulus in visual cortex and represented the results on images of the flattened cortical sheet. We used the method to locate visual areas and to evaluate the spatial precision of fMRI. Specifically, we: (i) identified the borders between several retinotopically organized visual areas in the posterior occipital lobe; (ii) measured the function relating cortical position to visual field eccentricity within area V1; (iii) localized activity to within 1.1 mm of visual cortex; and (iv) estimated the spatial resolution of the fMRI signal and found that signal amplitude falls to 60% at a spatial frequency of 1 cycle per 9 mm of visual cortex. This spatial resolution is consistent with a linespread whose full width at half maximum spreads across 3.5 mm of visual cortex. In a series of experiments, we measured the retinotopic organization of human cortical area V1 and identified the locations of other nearby retinotopically organized visual areas. We also used the retinotopic organization of human primary visual cortex to measure the spatial localization and spatial resolution that can be obtained from functional magnetic resonance imaging (fMRI) of human visual cortex. Human primary visual cortex (area V1) is located in the
1,585Â citations
TL;DR: In this article, the authors show that link communities are fundamental building blocks that reveal overlap and hierarchical organization in networks, and show that a large social network contains hierarchically organized community structures spanning inner-city to regional scales while maintaining pervasive overlap.
Abstract: Networks have become a key approach to understanding systems of interacting objects, unifying the study of diverse phenomena including biological organisms and human society. One crucial step when studying the structure and dynamics of networks is to identify communities: groups of related nodes that correspond to functional subunits such as protein complexes or social spheres. Communities in networks often overlap such that nodes simultaneously belong to several groups. Meanwhile, many networks are known to possess hierarchical organization, where communities are recursively grouped into a hierarchical structure. However, the fact that many real networks have communities with pervasive overlap, where each and every node belongs to more than one group, has the consequence that a global hierarchy of nodes cannot capture the relationships between overlapping groups. Here we reinvent communities as groups of links rather than nodes and show that this unorthodox approach successfully reconciles the antagonistic organizing principles of overlapping communities and hierarchy. In contrast to the existing literature, which has entirely focused on grouping nodes, link communities naturally incorporate overlap while revealing hierarchical organization. We find relevant link communities in many networks, including major biological networks such as protein-protein interaction and metabolic networks, and show that a large social network contains hierarchically organized community structures spanning inner-city to regional scales while maintaining pervasive overlap. Our results imply that link communities are fundamental building blocks that reveal overlap and hierarchical organization in networks to be two aspects of the same phenomenon.
1,534Â citations
31 Oct 1993
TL;DR: The authors have collected over 300 MRI volumetric datasets from normal individuals and transformed these datasets into stereotaxic space using a 3D linear re-sampling algorithm, and generated a series of statistical measures which express this population nonlinear variability in the form of parametric volumes.
Abstract: Recently, there has been a rapid growth in the use of 3D multi-modal correlative imaging for studies of the human brain Regional cerebral blood flow (CBF) changes indicate brain areas involved in stimulus processing These focal changes are often too small ( >
1,530Â citations
TL;DR: Automated calculation of whole-brain volume and estimated total intracranial volume are presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.
Abstract: The Open Access Series of Imaging Studies is a series of magnetic resonance imaging data sets that is publicly available for study and analysis. The initial data set consists of a cross-sectional collection of 416 subjects aged 18 to 96 years. One hundred of the included subjects older than 60 years have been clinically diagnosed with very mild to moderate Alzheimer's disease. The subjects are all right-handed and include both men and women. For each subject, three or four individual T1-weighted magnetic resonance imaging scans obtained in single imaging sessions are included. Multiple within-session acquisitions provide extremely high contrast-to-noise ratio, making the data amenable to a wide range of analytic approaches including automated computational analysis. Additionally, a reliability data set is included containing 20 subjects without dementia imaged on a subsequent visit within 90 days of their initial session. Automated calculation of whole-brain volume and estimated total intracranial volume are presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.
1,526Â citations